Adjusting system actions, user profiles and content in a social network based upon detected skipped relationships

ABSTRACT

Adjusting system actions based on an absence of relationship acceptance may include detecting absence of connection acceptance by one or more first users in a computer-implemented social networking system. Patterns of the absence of connection acceptance of the one or more first users may be correlated. Users with common patterns of absence of connection acceptance may be clustered into a cluster of users. Absence of connection acceptance by a second user may be detected. Responsive to determining that a pattern of the absence of connection acceptance associated with the second user matches with the common patterns, a profile associated with the second user may be updated according to a template profile associated with the cluster. System actions of the social networking system may be activated for the second user based on the profile updated according to the template profile.

FIELD

The present application relates generally to computers and computerapplications, and more particularly to social networking services andadjusting social networking system actions based on skippedrelationships.

BACKGROUND

Social networking platforms or services allow user to communicate via acomputer network, for example, in an online community, for example, toshare interests and activities. A user of a social networking platformmay create a profile that may include the information about the user, alist of one or more users designated as friends or connections forsharing online activities and others. Social networking applicationsthat provide social networking services now include a capability torecommend or suggest other users with whom a user may like to connect.For instance, when a user opens a browser or like user interface toactivate a social networking service, the social networking service maylook up other users who are participants of the social networkingservice who may have various commonalities with the user or those whohave indirect connections with the user, for suggesting a connection orrelationship.

BRIEF SUMMARY

A computer-implemented method and system of adjusting system actionsbased on an absence of relationship acceptance, may be provided. Themethod, in one aspect, may include detecting an absence of connectionacceptance by one or more first users in a computer-implemented socialnetworking system. The method may also include correlating patterns ofthe absence of connection acceptance of the one or more first users. Themethod may further include clustering users with common patterns ofabsence of connection acceptance into a cluster of users. The method mayalso include detecting an absence of connection acceptance by a seconduser. The method may also include, responsive to determining that apattern of the absence of connection acceptance associated with thesecond user matches with the common patterns, updating a profileassociated with the second user according to a template profileassociated with the cluster. The method may also include activatingsystem actions of the social networking system for the second user basedon the profile updated according to the template profile.

A system for adjusting system actions based on an absence ofrelationship acceptance, in one aspect, may include a storage device andone or more processors communicatively coupled to the storage device.One or more of the processors may be operable to detect an absence ofconnection acceptance by one or more first users in acomputer-implemented social networking system. One or more of theprocessors may be further operable to correlate patterns of the absenceof connection acceptance of the one or more first users. One or more ofthe processors may be further operable to cluster users with commonpatterns of absence of connection acceptance into a cluster of users.One or more of the processors may be further operable to detect anabsence of connection acceptance by a second user. Responsive todetermining that a pattern of the absence of connection acceptanceassociated with the second user matches with the common patterns, one ormore of the processors may be further operable to update a profileassociated with the second user according to a template profileassociated with the cluster. One or more of the processors may befurther operable to activate system actions of the social networkingsystem for the second user based on the profile updated according to thetemplate profile.

A computer readable storage medium storing a program of instructionsexecutable by a machine to perform one or more methods described hereinalso may be provided.

Further features as well as the structure and operation of variousembodiments are described in detail below with reference to theaccompanying drawings. In the drawings, like reference numbers indicateidentical or functionally similar elements.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow diagram illustrating an overview of a method in oneembodiment of the present disclosure.

FIG. 2 is a diagram showing an example of a methodology in oneembodiment of the present disclosure.

FIG. 3 shows a diagram illustrating a graph of social network users withconnections and skipped connections in one embodiment of the presentdisclosure.

FIG. 4 shows an example display provided to a user for determining aplurality of reasons and asking a user to confirm the reason in oneembodiment of the present disclosure.

FIG. 5 illustrates different groups of users depicting an examplescenario in one embodiment of the present disclosure.

FIG. 6 illustrates a schematic of an example computer or processingsystem that may implement a system that adjusts social networking systemactions based on skipped relationships in one embodiment of the presentdisclosure.

DETAILED DESCRIPTION

System and methods may be provided that improve the online socialnetwork platform or server, e.g., executing on one or more hardwareprocessors, by assessing or determining one or more reasons orinformation as to why users do not connect to other users, for example,even after repeated recommendations or suggestions by the socialnetwork. In one aspect, techniques are presented that correlate users ina social network in a computer-implemented communities based onnon-explicit avoidance of relationships.

In a social network, there are cases when two users close to one anotherdo not make a connection. In a simple example, two classmates may chooseto not “friend” one another on a social network. When this situationarises, social networks lack context to know whether the user will laterconnect with one another. There may be various reasons for notconnecting. For example, a user may choose to use one social network forbusiness relationships and another for personal relationships, and donot mix the two groups. As another example, a user may choose to skipcreating digital relationships with people that they already interactwith on a daily basis to minimize the number of communication channels.

For example, a personal social network may have a group of users who allknow one another in real life. This group of users may be very similarcharacteristics and connections as indicated by their social networkprofiles according to an automated analytics performed on the socialnetwork users. However, a number of users in the group may remaindisconnected and persistently skip suggestions to connect with otherusers.

For a potential connection that the social network rates as a goodsuggestion, if those users fail to connect after repeated suggestions,knowing the reason they are not connecting would be valuable, forexample, to the social network provider or developer, in providingrecommendations and content to those users.

FIG. 1 is a flow diagram illustrating an overview of a method in oneembodiment of the present disclosure. At 102, a social networkapplication or platform, for example, running on one or more hardwareprocessors such as a central processing unit (CPU) or another processor,performs analytics to determine that two users are likely to connect.Existing analytics may be used to perform such analysis. Informationabout the users, for example, user profiles may be stored in a databaseof users, on a storage device communicatively coupled to the one or morehardware processors.

At 104, the social network application recommends these connections tothe two users, for example, by presenting a notification on a userinterface display associated with the social network application. Forexample, a user's device may open a browser or the like user interfacefor allowing the user to interact with the social network applicationand communicate online with connected users or “friends” or the like.

At 106, the social network detects that users (e.g., one or more firstusers) are intentionally skipping the relationship. Whether the socialnetwork users are intentionally not connecting may be determined, forexample, using a methodology disclosed in a co-pending co-owned patentapplication, U.S. patent application Ser. No. 14/698,033 entitled“LEVERAGING SKIPPED RELATIONSHIPS IN A SOCIAL NETWORK,” incorporatedherein in its entirety, or using another method. For example, if a userdoes not connect despite repeated recommendations to connect, it may bedetermined that the user is intentionally skipping the connection.

At 108, the social network application or platform correlates the userskip pattern (pattern of absence of connection acceptance) with otherusers who have similar skip patterns.

At 110, the social network application clusters users with common skippatterns. For example, skip patterns of users may be stored by thesocial network application and the patterns analyzed to identify thoseusers having matching skip patterns. Matching in this disclosure neednot match identically. Rather, a match may be found if one user has apattern that matches a threshold percentage (e.g., 80% or another) oramount of pattern with another user.

At 112, the social network application may detect that another user(e.g., a second user) is skipping connection recommendations. Whenanother user (e.g., a second user), e.g., User Z, starts making the sameskip patterns, the social network application uses profiles of otherusers in the cluster as profile templates for User Z. For example, at114, responsive to determining that a pattern of the absence ofconnection acceptance associated with User Z matches with the commonskip patterns, User Z's profile may be updated according to a templateprofile associated with the cluster. A template profile associated withthe cluster, e.g., may be built to include common profiles of the usersin the cluster.

At 116, the social network application customizes experience for User Zbased on new correlations. For instance, social networking systemactions may be activated for the second user based on the profileupdated according to the template profile, such as: updating userrecommendations, displaying content, recommending groups, etc.

At 118, the social network application may determine the cause of theskipped relationship.

At 120, the social network application may apply the determined cause toother users in the cluster with confidence based on their clustermembership strength.

At 122, the social network application may customize experience based onnewly determined cause. For instance, if the determined reason for notconnecting is that a user does not mix professional connections andpersonal connections, the social network application may refrain fromrecommending a work colleague for relationship in a personal socialnetwork, and vice verse.

In one embodiment, the system and method of the present disclosurecorrelates users based on evidence of avoidance of relationships;customizes displayed content, recommendations, and other capabilitiesbased on the newly correlated users; determines the cause of skippedrelationships; customizes displayed content, recommendations, and othercapabilities for correlated users based specifically upon determinedcause; provides confidence based on graph interconnectedness; andeliminates outliers based on likely cause of connection.

FIG. 2 is a diagram showing an example of a methodology in oneembodiment of the present disclosure. Six users (e.g., User A, User B,User C, User D, User Y, User Z) work together at Acme Company and arefriends with one another. They frequently email one another, and theyhave a highly connected network graph within Acme Co's internal socialnetwork.

On a personal social network four users (User A, User B, User C, User D)routinely connect with business contacts on the personal network.However User Y prefers not to connect with business associates on theirpersonal network, even when they are good friends. The personal socialnetwork is able to determine that User Y should connect with User A,User B, User C, User D, and frequently recommends that User Y connectswith his associates. The social network application can make thisdetermination in multiple ways, for example, based on existingcapabilities.

For example, a personal social network application may pull in abusiness contact email list. The personal social network application maycorrelate other users that these five contacts have in common. Thepersonal social network may correlate similarities between the users,such as working for the same company in the same location. The personalsocial network application may extrapolate a hierarchy of Acme Company.The personal social network application may generate recommendationswith particular confidence values. The social network application maythen begin building up evidence that User Y is intentionally skippingrelationships with his associates, resulting in the example networkgraph shown in FIG. 2. For example, despite a number of recommendationsto User Y to connect to Users A, B, C and D, User Y still does notconnect. The dashed lines show skipped recommendations to connect.

User Z later joins the personal social network as a new user. The socialnetwork application makes a determination that User Z should connectwith users A, B, C, D and Y with a recommendation confidence. Like UserY, User Z does not want to connect with her work friends on the personalnetwork. New User Z skips opportunities to connect with users A, B, C, Dand Y. FIG. 3 shows a diagram illustrating a graph of social networkusers with connections and skipped connections in one embodiment of thepresent disclosure.

The social network application in one embodiment may correlate behaviorof skipped relationship and identify a similarity between users Y and Z.At this point the social network application may not know the reasonUsers Y and Z are skipping relationships, but the social networkapplication may make use of this information by correlating profiles.For example, the social network application in one embodiment maydeprioritize connection recommendations to User Z based on other usersthat User Y has intentionally skipped. If User Y has disabledcommunication from Acme Company on the personal social network, thesocial network application in one embodiment may deprioritize thatcontent for User Z. The social network application in one embodiment mayweight the profile correlation of User Y more highly than Users A, B, C,D, for example in suggesting groups to join and content to view. Thesocial network application in one embodiment may cluster the profiles ofUsers Y and Z, and other future users with similar recommendation skippatterns, to further strengthen similarities.

The social network in one embodiment of the present disclosure may alsodetermine or identify a cause for the skipped relationship. For example,it may be determined as to whether the users avoid certain types ofrelationships on certain networks; The users know one another, but theyhave a relationship that does not apply to the domain of the socialnetwork (such as not being friends, on a network of friends); The usersavoid making connections based on a profile aspect, such as commoninterests, other connections, company, location, etc.

In one aspect, the cause of users skipping relationships may bedetermined by presenting a free form entry and requesting a user toenter the reason.

In another aspect, the cause of users skipping relationships may bedetermined, for example, by an application running on a processor, whichcorrelates the user profile and skip patterns to other known causes ofusers skipping relationships. An example display provided to a user isshown in FIG. 4 for determining a plurality of reasons and asking a userto confirm the reason. The display may be provided on a computer userinterface.

For instance, analytics may be employed to determine the profilecharacteristic that the user is avoiding, such as company or location orinterests. A set of known causes may be pre-programmed into the socialnetwork application. An analytics threshold may also be pre-programmedto indicate when a user falls into such a category. This option may beparticularly relevant to networks that are used for a specific purpose,where a threshold can be added to make a determination when users wouldnot connect within the domain of the network. For example, for a networkbased on geographic location, the threshold would be based on distancebetween users to make a determination if a particular user connects onlywith nearby users.

Thus, in one embodiment, the social network application may identify thecause that the user is skipping relationship. Further, the socialnetwork application may utilize this information in several ways. Forexample, the social network application may determine applicability ofthe cause to other users in the cluster of users of the social network.For example, for users skipping connections with work colleagues, thesocial network application may check other users in the cluster anddetermine if those users have skipped work colleagues. The socialnetwork application may then add or remove users from the cluster basedon this known cause.

As another example, the social network application may update networkrecommendations based on the known (identified) cause. For example, thesocial network application may stop recommending work colleagues.

As yet another example, the social network application may reprioritizecontent and other recommendations in the system based on the known(identified) cause, where applicable.

Still as another example, the social network application may apply theidentified cause to other users in the cluster, and reprioritize contentand other recommendations in the system based on the known (identified)cause.

As another example, the social network application may use thedetermined cause to perform a more targeted determination from otherusers in the cluster. For example, the social network application mayfurther explicitly ask the user, “Is the reason you have not connectedwith User A due to the work relationship?—Yes.—No.” The user confirmedresponse then may be stored as the cause.

The social network application may also add the identified causeinformation to the user's implicit profile, to make use in existingprofile-based analytics.

The social network application may also ask other users to updateprofiles with specific determined information. For example, in theexample above, if User Z had not yet listed their company as Acme Co.,the clustering would indicate User Z is working at Acme Co. and thesocial network application may ask a targeted question such as: “Profileupdate: do you work at Acme Co.?” User Z's response may be used toupdate User Z's profile.

In one embodiment, the determined cause need not be acted onimmediately. For example, the social network application may construct abucket of users that fit a particular category and features and networkchanges may be implemented based on that cause. For example, if today asocial network has 10 users that do not interact with work colleagues,but later that number becomes 100,000, at that point the social networkapplication may take steps to improve the experience for those users. Inthe meantime, knowing which causes have arisen is still valuableinformation to prioritize development effort.

In one aspect, the social network's user connectedness may not always beconfigured such that one group of users are fully connected and anothergroup fully disjoint. In the example above, even if User Y avoids makingcontact with work colleagues, User Y may have connectivity to the otherusers for example through family relations or a community group. Inthese cases the social network application may determine a confidenceestimate based on the social network, where a user may be avoidingconnecting to a set of users, with a likelihood level. The estimatedconfidence can be used to affect the social network with strength basedon the confidence. For example, if User Y and User Z show similarbehavior in skipped relationships, but the system (or the social networkapplication) is only 60% confident that user Z matches the behavior ofUser Y, then the system can apply a 60% profile weight match rather thana direct correlation to the other profile. As a result, for example, thepredicted skipped relationships may be deprioritized as suggestions butnot fully eliminated as suggestions.

FIG. 5 illustrates different groups of users depicting this examplescenario in one embodiment of the present disclosure. In the exampleshown, User C is both co-worker and an interest group team member. UserC's team membership can override or partially override predicted skippedrelationship. A formed connection with User C does not mean User Ystopped connecting with work colleagues.

Determining the cause of a connection is also valuable in “cleaning up”the social network graph. For example a community group may go on aretreat, and all those members may connect with one another during theretreat. If the connection breaks one of the previously identifiedskipped relationships, the connection may be considered an outlier fromthe user's normal behavior. In this case, the connection may bediscarded from the profile matching.

In one aspect, the following type of connection behavior may be detectedand analyzed: temporal aspects, such as a group of users connecting atthe same time; relationship aspects, such as a user connecting throughanother user known to be part of a group (e.g., an interest group)outside the source of the user's skipped behavior (e.g., workcolleagues). Connections in the group can be analyzed with respect tothese aspects to identify outliers and raise confidence of a user'sskipped relationship behavior. For instance, the users who do not fitthe type of connection behavior, such as those who do not fit into thetemporal aspect or the another relationship aspect, would be consideredoutliers.

In addition, the outliers can be used as examples where the user doesnot skip relationships, which can further enhance a recommendationengine, for example, of the social network application, by refining theset of users likely to connect with, with the set of users likely to beskipped. For instance, once the outliers are identified and alsoanalyzed to assess the reason why the user skipped relationships, therecommendation engine can be refined by using these reasons tounderstand the set of users that the user may want or not want toconnect with.

In one aspect, a method for adjusting system actions may be based on anabsence of relationship acceptance attributed to a cause or reason toform a classification of a pattern of activity. For example, an absenceof relationship acceptance between users may be analyzed against a setof social connection aspects in a social networking system. Responsiveto determining that an absence of relationship acceptance between afirst set of users and a second set of users with a first socialconnection aspect exceeds a predetermined threshold, profiles of thefirst set of users and the second set of users with the first socialconnection aspect may be updated by the social networking system. Socialcontent may be tailored to the first set of users and the second set ofusers based on the first social connection aspect. The set of socialconnection aspects may include one or more of business contactrelationship, location, common interest, another community connection,demography, and others. The set of social connection aspects may bedetermined by natural language processing (NLP) and analytic analysis ofcommunications and profiles of the first set of users and the second setof users. The set of social connection aspects may be determined by thesocial networking system interacting with the first set of users and thesecond set of users. The tailoring social content may include adjustingor tuning algorithms that process contact requests, information contentpostings, and contact relationship, and others.

FIG. 6 illustrates a schematic of an example computer or processingsystem that may implement a system that adjusts social networking systemactions based on skipped relationships in one embodiment of the presentdisclosure. The computer system is only one example of a suitableprocessing system and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the methodologydescribed herein. The processing system shown may be operational withnumerous other general purpose or special purpose computing systemenvironments or configurations. Examples of well-known computingsystems, environments, and/or configurations that may be suitable foruse with the processing system shown in FIG. 6 may include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, handheld or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

The computer system may be described in the general context of computersystem executable instructions, such as program modules, being executedby a computer system. Generally, program modules may include routines,programs, objects, components, logic, data structures, and so on thatperform particular tasks or implement particular abstract data types.The computer system may be practiced in distributed cloud computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. In a distributed cloudcomputing environment, program modules may be located in both local andremote computer system storage media including memory storage devices.

The components of computer system may include, but are not limited to,one or more processors or processing units 12, a system memory 16, and abus 14 that couples various system components including system memory 16to processor 12. The processor 12 may include a module 10 that performsthe methods described herein. The module 10 may be programmed into theintegrated circuits of the processor 12, or loaded from memory 16,storage device 18, or network 24 or combinations thereof.

Bus 14 may represent one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system may include a variety of computer system readable media.Such media may be any available media that is accessible by computersystem, and it may include both volatile and non-volatile media,removable and non-removable media.

System memory 16 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) and/or cachememory or others. Computer system may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 18 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(e.g., a “hard drive”). Although not shown, a magnetic disk drive forreading from and writing to a removable, non-volatile magnetic disk(e.g., a “floppy disk”), and an optical disk drive for reading from orwriting to a removable, non-volatile optical disk such as a CD-ROM,DVD-ROM or other optical media can be provided. In such instances, eachcan be connected to bus 14 by one or more data media interfaces.

Computer system may also communicate with one or more external devices26 such as a keyboard, a pointing device, a display 28, etc.; one ormore devices that enable a user to interact with computer system; and/orany devices (e.g., network card, modem, etc.) that enable computersystem to communicate with one or more other computing devices. Suchcommunication can occur via Input/Output (I/O) interfaces 20.

Still yet, computer system can communicate with one or more networks 24such as a local area network (LAN), a general wide area network (WAN),and/or a public network (e.g., the Internet) via network adapter 22. Asdepicted, network adapter 22 communicates with the other components ofcomputer system via bus 14. It should be understood that although notshown, other hardware and/or software components could be used inconjunction with computer system. Examples include, but are not limitedto: microcode, device drivers, redundant processing units, external diskdrive arrays, RAID systems, tape drives, and data archival storagesystems, etc.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements, if any, in the claims below areintended to include any structure, material, or act for performing thefunction in combination with other claimed elements as specificallyclaimed. The description of the present invention has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the invention in the form disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.The embodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

What is claimed is:
 1. A computer-implemented method executedautomatically by a social network application running on a hardwareprocessor, the method comprising: detecting absence of connectionacceptance by a plurality of users in a computer-implemented socialnetworking system despite repeated recommendations by the social networkapplication to connect; correlating patterns of the absence ofconnection acceptance of the plurality of users; clustering theplurality of users with common patterns of absence of connectionacceptance into a cluster of users; detecting absence of connectionacceptance by another user, wherein said another user is a differentuser from the plurality of users; determining a cause of the skippedrelationship; and applying the cause to a user in the cluster with aconfidence value according to membership strength of the user in thecluster.
 2. The method of claim 1, further including: responsive todetermining that a pattern of the absence of connection acceptanceassociated with said another user matches with the common patterns ofthe absence of connection acceptance by the plurality of users, updatinga profile associated with said another user according to a templateprofile associated with the cluster, the template profile generated toinclude a profile common among the plurality of users belonging to thecluster; and activating a system action of the social networking systemfor said another user based on the profile updated according to thetemplate profile.
 3. The method of claim 2, wherein the system actionincludes recommending a connection.
 4. The method of claim 2, whereinthe system action includes causing displaying of customized content. 5.The method of claim 1, further including modifying a system action ofthe social networking system based on the cause.
 6. The method of claim5, wherein the system action includes updating a set of users likely toconnect with and a set of users likely to be skipped based on thedetermined cause.
 7. A computer program product comprising a computerreadable storage medium having program instructions embodied therewith,the program instructions executable by a device to cause the device to:detect absence of connection acceptance by a plurality of users in acomputer-implemented social networking system despite repeatedrecommendations by the social network application to connect; correlatepatterns of the absence of connection acceptance of the plurality ofusers; cluster the plurality of users with common patterns of absence ofconnection acceptance into a cluster of users; detect absence ofconnection acceptance by another user, wherein said another user is adifferent user from the plurality of users; determine a cause of theskipped relationship; and apply the cause to a user in the cluster witha confidence value according to membership strength of the user in thecluster.
 8. The computer program product of claim 7, wherein responsiveto determining that a pattern of the absence of connection acceptanceassociated with said another user matches with the common patterns ofthe absence of connection acceptance by the plurality of users, thedevice is caused to update a profile associated with said another useraccording to a template profile associated with the cluster, thetemplate profile generated to include a profile common among theplurality of users belonging to the cluster.
 9. The computer programproduct of claim 8, wherein the device is further caused to activate asystem action of the social networking system for said another userbased on the profile updated according to the template profile.
 10. Thecomputer program product of claim 9, wherein the system action includesrecommending connections.
 11. The computer program product of claim 9,wherein the system action includes causing displaying of customizedcontent.
 12. The computer program product of claim 9, further includingmodifying a system action of the social networking system based on thecause.
 13. The computer program product of claim 12, wherein the systemaction includes updating a set of users likely to connect with and a setof user likely to be skipped based on the determined cause.
 14. A systemfor adjusting a system action based on an absence of relationshipacceptance, comprising: a storage device; and a processorcommunicatively coupled to the storage device, the processor running asocial network application operable to detect absence of connectionacceptance by a plurality of users in a computer-implemented socialnetworking system despite repeated recommendations by the social networkapplication to connect, the processor further operable to correlatepatterns of the absence of connection acceptance of the plurality ofusers, the processor further operable to cluster the plurality of userswith common patterns of absence of connection acceptance into a clusterof users, the processor further operable to detect absence of connectionacceptance by another user, wherein said another user is a differentuser from the plurality of users, the processor further operable todetermine a cause of the skipped relationship, and the processor furtheroperable to apply the cause to the users in the cluster.
 15. The systemof claim 14, wherein the processor is further operable to modify asystem action of the social networking system based on the cause. 16.The system of claim 14, wherein responsive to determining that a patternof the absence of connection acceptance associated with said anotheruser matches with the common patterns of the absence of connectionacceptance by the plurality of users, the processor is further operableto update a profile associated with said another user according to atemplate profile associated with the cluster, the template profilegenerated to include a profile common among the plurality of usersbelonging to the cluster, and the processor is further operable toactivate a system action of the social networking system for saidanother user based on the profile updated according to the templateprofile.
 17. The system of claim 16, wherein the system action includesrecommending a connection.
 18. The system of claim 16, wherein thesystem action includes causing displaying of customized content.
 19. Thesystem of claim 16, wherein the system action includes updating a set ofusers likely to connect with and a set of user likely to be skippedbased on the determined cause.